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Explainable ai: A review of machine learning interpretability methods
Recent advances in artificial intelligence (AI) have led to its widespread industrial adoption,
with machine learning systems demonstrating superhuman performance in a significant …
with machine learning systems demonstrating superhuman performance in a significant …
–Omic and electronic health record big data analytics for precision medicine
Objective: Rapid advances of high-throughput technologies and wide adoption of electronic
health records (EHRs) have led to fast accumulation of–omic and EHR data. These …
health records (EHRs) have led to fast accumulation of–omic and EHR data. These …
[HTML][HTML] Machine learning of neuroimaging for assisted diagnosis of cognitive impairment and dementia: a systematic review
Introduction Advanced machine learning methods might help to identify dementia risk from
neuroimaging, but their accuracy to date is unclear. Methods We systematically reviewed the …
neuroimaging, but their accuracy to date is unclear. Methods We systematically reviewed the …
Machine learning in healthcare: review, opportunities and challenges
Abstract Machine learning technology is a prominent research field aiming to build a system
which imitates human intelligence. Machine learning can be applied in the healthcare …
which imitates human intelligence. Machine learning can be applied in the healthcare …
Privft: Private and fast text classification with homomorphic encryption
We present an efficient and non-interactive method for Text Classification while preserving
the privacy of the content using Fully Homomorphic Encryption (FHE). Our solution (named …
the privacy of the content using Fully Homomorphic Encryption (FHE). Our solution (named …
Artificial intelligence for internet of things and enhanced medical systems
Abstract Internet of things (IoT), Big Data, and artificial intelligence (AI) are related research
fields that have a relevant impact factor on the design and development of enhanced …
fields that have a relevant impact factor on the design and development of enhanced …
[HTML][HTML] Convolution neural network–based Alzheimer's disease classification using hybrid enhanced independent component analysis based segmented gray matter …
In recent times, accurate and early diagnosis of Alzheimer's disease (AD) plays a vital role in
patient care and further treatment. Predicting AD from mild cognitive impairment (MCI) and …
patient care and further treatment. Predicting AD from mild cognitive impairment (MCI) and …
Deep Neural Network Based Ensemble learning Algorithms for the healthcare system (diagnosis of chronic diseases)
learning algorithms. In this paper, we review the classification algorithms used in the health
care system (chronic diseases) and present the neural network-based Ensemble learning …
care system (chronic diseases) and present the neural network-based Ensemble learning …
[ספר][B] Industrial applications of machine learning
P Larrañaga, D Atienza, J Diaz-Rozo, A Ogbechie… - 2018 - taylorfrancis.com
Industrial Applications of Machine Learning shows how machine learning can be applied to
address real-world problems in the fourth industrial revolution, and provides the required …
address real-world problems in the fourth industrial revolution, and provides the required …
Application of Gabor wavelet and Locality Sensitive Discriminant Analysis for automated identification of breast cancer using digitized mammogram images
Breast cancer is one of the prime causes of death in women. Early detection may help to
improve the survival rate to a great extent. Mammography is considered as one of the most …
improve the survival rate to a great extent. Mammography is considered as one of the most …